40 citations · 70 across the 24 of their papers we have counts for
3 papers · 1 filter
Many-core algorithms for high-dimensional gradients on phylogenetic trees
Karthik Gangavarapu, Xiang Ji, Guy Baele +4
The rapid growth in genomic pathogen data spurs the need for efficient inference techniques, such as Hamiltonian Monte Carlo (HMC) in a Bayesian framework, to estimate parameters o…
Gradients do grow on trees: a linear-time -dimensional gradient for statistical phylogenetics
Xiang Ji, Zhenyu Zhang, Andrew Holbrook +5
Calculation of the log-likelihood stands as the computational bottleneck for many statistical phylogenetic algorithms. Even worse is its gradient evaluation, often used to target r…
Massive parallelization boosts big Bayesian multidimensional scaling
Andrew Holbrook, Philippe Lemey, Guy Baele +4
Big Bayes is the computationally intensive co-application of big data and large, expressive Bayesian models for the analysis of complex phenomena in scientific inference and statis…